Overview

Dataset statistics

Number of variables13
Number of observations377
Missing cells57
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.8 KiB
Average record size in memory108.0 B

Variable types

Numeric12
Categorical1

Alerts

Close is highly overall correlated with High and 4 other fieldsHigh correlation
High is highly overall correlated with Close and 4 other fieldsHigh correlation
Low is highly overall correlated with Close and 4 other fieldsHigh correlation
MA_10 is highly overall correlated with Close and 4 other fieldsHigh correlation
MA_20 is highly overall correlated with Close and 4 other fieldsHigh correlation
Open is highly overall correlated with Close and 4 other fieldsHigh correlation
Return is highly overall correlated with open-closeHigh correlation
Volume is highly overall correlated with low-highHigh correlation
low-high is highly overall correlated with VolumeHigh correlation
open-close is highly overall correlated with ReturnHigh correlation
MA_10 has 9 (2.4%) missing valuesMissing
Volatility_10 has 9 (2.4%) missing valuesMissing
MA_20 has 19 (5.0%) missing valuesMissing
Volatility_20 has 19 (5.0%) missing valuesMissing
Volume has unique valuesUnique

Reproduction

Analysis started2024-07-04 03:51:24.609409
Analysis finished2024-07-04 03:51:42.681241
Duration18.07 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

Open
Real number (ℝ)

HIGH CORRELATION 

Distinct361
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.52265
Minimum126.01
Maximum220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-03T23:51:42.789414image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum126.01
5-th percentile143.81
Q1169.03
median177.7
Q3189.33
95-th percentile196.372
Maximum220
Range93.989998
Interquartile range (IQR)20.300003

Descriptive statistics

Standard deviation17.327144
Coefficient of variation (CV)0.098158188
Kurtosis0.52549196
Mean176.52265
Median Absolute Deviation (MAD)10.580002
Skewness-0.5250557
Sum66549.04
Variance300.22991
MonotonicityNot monotonic
2024-07-03T23:51:42.951461image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
181.2700043 3
 
0.8%
182.3500061 2
 
0.5%
176.4799957 2
 
0.5%
195.0899963 2
 
0.5%
191.4100037 2
 
0.5%
189.8399963 2
 
0.5%
171.75 2
 
0.5%
191.5700073 2
 
0.5%
184.8999939 2
 
0.5%
189.3300018 2
 
0.5%
Other values (351) 356
94.4%
ValueCountFrequency (%)
126.0100021 1
0.3%
126.8899994 1
0.3%
127.1299973 1
0.3%
130.2599945 1
0.3%
130.2799988 1
0.3%
130.4700012 1
0.3%
131.25 1
0.3%
132.0299988 1
0.3%
133.8800049 1
0.3%
134.0800018 1
0.3%
ValueCountFrequency (%)
220 1
0.3%
217.5899963 1
0.3%
216.1499939 1
0.3%
215.7700043 1
0.3%
214.7400055 1
0.3%
214.6900024 1
0.3%
213.9299927 1
0.3%
213.8500061 1
0.3%
213.3699951 1
0.3%
212.0899963 1
0.3%

High
Real number (ℝ)

HIGH CORRELATION 

Distinct365
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean178.17568
Minimum127.77
Maximum221.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-03T23:51:43.106438image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum127.77
5-th percentile146.398
Q1170.45
median179.63
Q3190.07001
95-th percentile198.046
Maximum221.55
Range93.780006
Interquartile range (IQR)19.62001

Descriptive statistics

Standard deviation17.294943
Coefficient of variation (CV)0.097066804
Kurtosis0.5905372
Mean178.17568
Median Absolute Deviation (MAD)10.290009
Skewness-0.4513424
Sum67172.23
Variance299.11507
MonotonicityNot monotonic
2024-07-03T23:51:43.272581image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196.6300049 2
 
0.5%
174.0299988 2
 
0.5%
189.9900055 2
 
0.5%
187.1000061 2
 
0.5%
174.3000031 2
 
0.5%
187.0500031 2
 
0.5%
147.2299957 2
 
0.5%
180.1199951 2
 
0.5%
182.7599945 2
 
0.5%
194.3999939 2
 
0.5%
Other values (355) 357
94.7%
ValueCountFrequency (%)
127.7699966 1
0.3%
128.6600037 1
0.3%
130.2899933 1
0.3%
130.8999939 1
0.3%
131.2599945 1
0.3%
133.4100037 1
0.3%
133.5099945 1
0.3%
134.2599945 1
0.3%
134.9199982 1
0.3%
136.25 1
0.3%
ValueCountFrequency (%)
221.5500031 1
0.3%
220.3800049 1
0.3%
220.1999969 1
0.3%
218.9499969 1
0.3%
218.6300049 1
0.3%
217.5099945 1
0.3%
216.75 1
0.3%
216.0700073 1
0.3%
215.7400055 1
0.3%
215.1699982 1
0.3%

Low
Real number (ℝ)

HIGH CORRELATION 

Distinct372
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean175.16459
Minimum124.17
Maximum219.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-03T23:51:43.434771image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum124.17
5-th percentile142.736
Q1168
median176.57001
Q3187.78
95-th percentile195.264
Maximum219.03
Range94.860001
Interquartile range (IQR)19.779999

Descriptive statistics

Standard deviation17.228465
Coefficient of variation (CV)0.098355868
Kurtosis0.57082689
Mean175.16459
Median Absolute Deviation (MAD)10.360001
Skewness-0.56182544
Sum66037.05
Variance296.82001
MonotonicityNot monotonic
2024-07-03T23:51:43.602846image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
177.6000061 2
 
0.5%
194.1399994 2
 
0.5%
172.0500031 2
 
0.5%
182.4400024 2
 
0.5%
170.7599945 2
 
0.5%
191.0899963 1
 
0.3%
181.5 1
 
0.3%
180.1699982 1
 
0.3%
180.8800049 1
 
0.3%
183.4299927 1
 
0.3%
Other values (362) 362
96.0%
ValueCountFrequency (%)
124.1699982 1
0.3%
124.7600021 1
0.3%
124.8899994 1
0.3%
125.0800018 1
0.3%
128.1199951 1
0.3%
129.8899994 1
0.3%
130.4600067 1
0.3%
131.4400024 1
0.3%
131.6600037 1
0.3%
133.7700043 1
0.3%
ValueCountFrequency (%)
219.0299988 1
0.3%
215.1000061 1
0.3%
213 1
0.3%
212.7200012 1
0.3%
212.3500061 1
0.3%
211.9199982 1
0.3%
211.6000061 1
0.3%
211.3000031 1
0.3%
210.6399994 1
0.3%
210.3000031 1
0.3%

Close
Real number (ℝ)

HIGH CORRELATION 

Distinct364
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.75347
Minimum125.02
Maximum221.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-03T23:51:43.760734image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum125.02
5-th percentile145.106
Q1169
median178.17999
Q3189.41
95-th percentile197.066
Maximum221.55
Range96.530006
Interquartile range (IQR)20.410004

Descriptive statistics

Standard deviation17.2165
Coefficient of variation (CV)0.097404026
Kurtosis0.5997314
Mean176.75347
Median Absolute Deviation (MAD)10.179993
Skewness-0.50514178
Sum66636.06
Variance296.40788
MonotonicityNot monotonic
2024-07-03T23:51:43.919869image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
179.8000031 2
 
0.5%
194.5 2
 
0.5%
175.8399963 2
 
0.5%
178.8500061 2
 
0.5%
172.6900024 2
 
0.5%
172.0700073 2
 
0.5%
173 2
 
0.5%
176.0800018 2
 
0.5%
177.9700012 2
 
0.5%
173.75 2
 
0.5%
Other values (354) 357
94.7%
ValueCountFrequency (%)
125.0199966 1
0.3%
125.0699997 1
0.3%
126.3600006 1
0.3%
129.6199951 1
0.3%
130.1499939 1
0.3%
130.7299957 1
0.3%
133.4100037 1
0.3%
133.4900055 1
0.3%
134.7599945 1
0.3%
135.2100067 1
0.3%
ValueCountFrequency (%)
221.5500031 1
0.3%
220.2700043 1
0.3%
216.75 1
0.3%
216.6699982 1
0.3%
214.2899933 1
0.3%
214.2400055 1
0.3%
214.1000061 1
0.3%
213.25 1
0.3%
213.0700073 1
0.3%
212.4900055 1
0.3%

Volume
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct377
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61135131
Minimum24048300
Maximum2.464214 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-03T23:51:44.080774image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum24048300
5-th percentile40836740
Q148088700
median54945800
Q367772100
95-th percentile99947360
Maximum2.464214 × 108
Range2.223731 × 108
Interquartile range (IQR)19683400

Descriptive statistics

Standard deviation22873021
Coefficient of variation (CV)0.37413874
Kurtosis17.149158
Mean61135131
Median Absolute Deviation (MAD)9174300
Skewness3.2341452
Sum2.3047944 × 1010
Variance5.2317509 × 1014
MonotonicityNot monotonic
2024-07-03T23:51:44.243018image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112117500 1
 
0.3%
34049900 1
 
0.3%
49128400 1
 
0.3%
46792900 1
 
0.3%
42841800 1
 
0.3%
59144500 1
 
0.3%
62303300 1
 
0.3%
71983600 1
 
0.3%
58414500 1
 
0.3%
82488700 1
 
0.3%
Other values (367) 367
97.3%
ValueCountFrequency (%)
24048300 1
0.3%
28919300 1
0.3%
31458200 1
0.3%
34049900 1
0.3%
34648500 1
0.3%
35175100 1
0.3%
36294600 1
0.3%
37122800 1
0.3%
37266700 1
0.3%
37283200 1
0.3%
ValueCountFrequency (%)
246421400 1
0.3%
198134300 1
0.3%
172373300 1
0.3%
163224100 1
0.3%
154357300 1
0.3%
136682600 1
0.3%
128256700 1
0.3%
121946500 1
0.3%
121664700 1
0.3%
118339000 1
0.3%

open-close
Real number (ℝ)

HIGH CORRELATION 

Distinct309
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.23082217
Minimum-13.5
Maximum5.6800079
Zeros0
Zeros (%)0.0%
Negative210
Negative (%)55.7%
Memory size5.9 KiB
2024-07-03T23:51:44.403179image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-13.5
5-th percentile-2.9900055
Q1-1.4900055
median-0.13999939
Q31.0200043
95-th percentile2.9220032
Maximum5.6800079
Range19.180008
Interquartile range (IQR)2.5100098

Descriptive statistics

Standard deviation2.0116398
Coefficient of variation (CV)-8.7151063
Kurtosis5.0322089
Mean-0.23082217
Median Absolute Deviation (MAD)1.2299957
Skewness-0.73711105
Sum-87.019958
Variance4.0466945
MonotonicityNot monotonic
2024-07-03T23:51:44.564637image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5599975586 4
 
1.1%
1.080001831 3
 
0.8%
-0.3600006104 3
 
0.8%
-0.04000854492 3
 
0.8%
0.08000183105 3
 
0.8%
-0.1399993896 3
 
0.8%
-0.1100006104 3
 
0.8%
1.229995728 2
 
0.5%
1.550003052 2
 
0.5%
0.0299987793 2
 
0.5%
Other values (299) 349
92.6%
ValueCountFrequency (%)
-13.5 1
0.3%
-6.699996948 1
0.3%
-6.470001221 1
0.3%
-5.990005493 1
0.3%
-5.700012207 1
0.3%
-4.660003662 1
0.3%
-4.419998169 1
0.3%
-4.120010376 1
0.3%
-4.009994507 1
0.3%
-3.929992676 1
0.3%
ValueCountFrequency (%)
5.680007935 1
0.3%
5.489990234 1
0.3%
5.209999084 1
0.3%
5.150009155 1
0.3%
4.289993286 1
0.3%
4.25 1
0.3%
4.099990845 1
0.3%
3.779998779 1
0.3%
3.769989014 1
0.3%
3.529998779 1
0.3%

low-high
Real number (ℝ)

HIGH CORRELATION 

Distinct272
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.0110877
Minimum-13.529999
Maximum-0.95999146
Zeros0
Zeros (%)0.0%
Negative377
Negative (%)100.0%
Memory size5.9 KiB
2024-07-03T23:51:44.849282image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-13.529999
5-th percentile-5.4440033
Q1-3.3799896
median-2.7000122
Q3-2.2200012
95-th percentile-1.4860046
Maximum-0.95999146
Range12.570007
Interquartile range (IQR)1.1599884

Descriptive statistics

Standard deviation1.4195068
Coefficient of variation (CV)-0.47142659
Kurtosis16.005455
Mean-3.0110877
Median Absolute Deviation (MAD)0.5900116
Skewness-2.9766445
Sum-1135.1801
Variance2.0149995
MonotonicityNot monotonic
2024-07-03T23:51:45.053832image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.580001831 5
 
1.3%
-2.419998169 4
 
1.1%
-2.330001831 4
 
1.1%
-1.809997559 4
 
1.1%
-2.130004883 4
 
1.1%
-2.660003662 4
 
1.1%
-2.820007324 4
 
1.1%
-2.520004272 3
 
0.8%
-3.330001831 3
 
0.8%
-3.089996338 3
 
0.8%
Other values (262) 339
89.9%
ValueCountFrequency (%)
-13.52999878 1
0.3%
-13.30000305 1
0.3%
-9.550003052 1
0.3%
-8.080001831 1
0.3%
-7.380004883 1
0.3%
-7.300003052 1
0.3%
-6.910003662 1
0.3%
-6.729995728 1
0.3%
-6.650009155 1
0.3%
-6.229995728 1
0.3%
ValueCountFrequency (%)
-0.9599914551 1
0.3%
-1.059997559 2
0.5%
-1.11000061 1
0.3%
-1.130004883 1
0.3%
-1.199996948 1
0.3%
-1.230010986 1
0.3%
-1.260009766 1
0.3%
-1.339996338 1
0.3%
-1.36000061 1
0.3%
-1.399993896 1
0.3%

MA_10
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct368
Distinct (%)100.0%
Missing9
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean176.87064
Minimum130.455
Maximum213.092
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-03T23:51:45.237214image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum130.455
5-th percentile148.6258
Q1170.044
median177.544
Q3188.74125
95-th percentile195.7102
Maximum213.092
Range82.637003
Interquartile range (IQR)18.697249

Descriptive statistics

Standard deviation15.647832
Coefficient of variation (CV)0.088470489
Kurtosis0.38658574
Mean176.87064
Median Absolute Deviation (MAD)9.7294983
Skewness-0.56775582
Sum65088.395
Variance244.85464
MonotonicityNot monotonic
2024-07-03T23:51:45.396889image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192.225 1
 
0.3%
184.2049988 1
 
0.3%
184.5009995 1
 
0.3%
185.3909988 1
 
0.3%
186.1569992 1
 
0.3%
186.912999 1
 
0.3%
187.598999 1
 
0.3%
188.4449997 1
 
0.3%
189.3569992 1
 
0.3%
190.7220001 1
 
0.3%
Other values (358) 358
95.0%
(Missing) 9
 
2.4%
ValueCountFrequency (%)
130.4549988 1
0.3%
131.4689995 1
0.3%
132.3599998 1
0.3%
133.6449997 1
0.3%
134.7940002 1
0.3%
136.0320007 1
0.3%
137.1450012 1
0.3%
138.1920013 1
0.3%
139.4440002 1
0.3%
140.2680008 1
0.3%
ValueCountFrequency (%)
213.0920013 1
0.3%
212.3660004 1
0.3%
212.0059998 1
0.3%
211.9420013 1
0.3%
211.8390015 1
0.3%
211.5800003 1
0.3%
211.2290009 1
0.3%
209.6339996 1
0.3%
208.5089996 1
0.3%
207.2079987 1
0.3%

Volatility_10
Real number (ℝ)

MISSING 

Distinct368
Distinct (%)100.0%
Missing9
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean3.0894073
Minimum0.7065527
Maximum9.7076821
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-03T23:51:45.551452image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.7065527
5-th percentile1.3272386
Q12.0480656
median2.7583988
Q33.6507659
95-th percentile5.9396041
Maximum9.7076821
Range9.0011294
Interquartile range (IQR)1.6027003

Descriptive statistics

Standard deviation1.5255676
Coefficient of variation (CV)0.49380592
Kurtosis3.1044229
Mean3.0894073
Median Absolute Deviation (MAD)0.74457686
Skewness1.5485886
Sum1136.9019
Variance2.3273565
MonotonicityNot monotonic
2024-07-03T23:51:45.709382image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.046439716 1
 
0.3%
1.78219215 1
 
0.3%
1.746211738 1
 
0.3%
3.040988663 1
 
0.3%
4.001956085 1
 
0.3%
4.558337888 1
 
0.3%
4.937837281 1
 
0.3%
5.188110002 1
 
0.3%
5.420976107 1
 
0.3%
4.818262532 1
 
0.3%
Other values (358) 358
95.0%
(Missing) 9
 
2.4%
ValueCountFrequency (%)
0.7065526953 1
0.3%
0.7464511512 1
0.3%
0.7770942862 1
0.3%
0.997711032 1
0.3%
1.007812161 1
0.3%
1.141057073 1
0.3%
1.146558179 1
0.3%
1.149849541 1
0.3%
1.203617492 1
0.3%
1.212298882 1
0.3%
ValueCountFrequency (%)
9.70768208 1
0.3%
9.590580109 1
0.3%
8.995092392 1
0.3%
8.971839121 1
0.3%
8.529783193 1
0.3%
8.111752601 1
0.3%
7.894354199 1
0.3%
7.78600246 1
0.3%
7.680089739 1
0.3%
7.105134617 1
0.3%

MA_20
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct358
Distinct (%)100.0%
Missing19
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean176.97428
Minimum135.779
Maximum209.4595
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-03T23:51:45.864657image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum135.779
5-th percentile150.31315
Q1170.9125
median178.63675
Q3188.15275
95-th percentile193.85213
Maximum209.4595
Range73.680501
Interquartile range (IQR)17.240248

Descriptive statistics

Standard deviation14.131809
Coefficient of variation (CV)0.079852335
Kurtosis0.17509855
Mean176.97428
Median Absolute Deviation (MAD)9.0699997
Skewness-0.68048828
Sum63356.791
Variance199.70803
MonotonicityNot monotonic
2024-07-03T23:51:46.037036image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193.3185005 1
 
0.3%
188.1179993 1
 
0.3%
188.1649994 1
 
0.3%
188.4339996 1
 
0.3%
188.7969994 1
 
0.3%
189.5415001 1
 
0.3%
190.2654999 1
 
0.3%
190.8675003 1
 
0.3%
191.3235008 1
 
0.3%
191.6730003 1
 
0.3%
Other values (348) 348
92.3%
(Missing) 19
 
5.0%
ValueCountFrequency (%)
135.7789993 1
0.3%
136.796999 1
0.3%
138.0199993 1
0.3%
139.4939995 1
0.3%
140.5994995 1
0.3%
141.8244995 1
0.3%
142.8839996 1
0.3%
143.7529991 1
0.3%
144.6329987 1
0.3%
145.5874992 1
0.3%
ValueCountFrequency (%)
209.4595001 1
0.3%
208.0995003 1
0.3%
206.7875 1
0.3%
205.5625 1
0.3%
204.5959999 1
0.3%
203.4054993 1
0.3%
202.2424995 1
0.3%
201.287999 1
0.3%
200.2249992 1
0.3%
199.3954987 1
0.3%

Volatility_20
Real number (ℝ)

MISSING 

Distinct358
Distinct (%)100.0%
Missing19
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean4.4344414
Minimum2.0074068
Maximum10.277889
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-03T23:51:46.205405image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2.0074068
5-th percentile2.4609049
Q13.0187342
median3.8834756
Q35.3002588
95-th percentile8.3726044
Maximum10.277889
Range8.2704825
Interquartile range (IQR)2.2815246

Descriptive statistics

Standard deviation1.8341298
Coefficient of variation (CV)0.41361012
Kurtosis0.58415232
Mean4.4344414
Median Absolute Deviation (MAD)0.99922912
Skewness1.124259
Sum1587.53
Variance3.3640323
MonotonicityNot monotonic
2024-07-03T23:51:46.370009image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.05019438 1
 
0.3%
4.61875227 1
 
0.3%
4.684888309 1
 
0.3%
5.031703877 1
 
0.3%
5.301245993 1
 
0.3%
5.440700631 1
 
0.3%
5.574439578 1
 
0.3%
5.728447551 1
 
0.3%
5.648666323 1
 
0.3%
5.529309235 1
 
0.3%
Other values (348) 348
92.3%
(Missing) 19
 
5.0%
ValueCountFrequency (%)
2.007406816 1
0.3%
2.073079146 1
0.3%
2.099920143 1
0.3%
2.103446065 1
0.3%
2.124086832 1
0.3%
2.127306029 1
0.3%
2.216914316 1
0.3%
2.25644592 1
0.3%
2.270771667 1
0.3%
2.325729754 1
0.3%
ValueCountFrequency (%)
10.27788934 1
0.3%
10.22548723 1
0.3%
10.09407565 1
0.3%
9.863836597 1
0.3%
9.632940923 1
0.3%
9.505026532 1
0.3%
9.478695098 1
0.3%
9.236876034 1
0.3%
8.770866715 1
0.3%
8.632305054 1
0.3%

Return
Real number (ℝ)

HIGH CORRELATION 

Distinct376
Distinct (%)100.0%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean0.00161436
Minimum-0.048020049
Maximum0.072649126
Zeros1
Zeros (%)0.3%
Negative170
Negative (%)45.1%
Memory size5.9 KiB
2024-07-03T23:51:46.528515image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.048020049
5-th percentile-0.019152647
Q1-0.0069333593
median0.0015522883
Q30.0087628992
95-th percentile0.021892529
Maximum0.072649126
Range0.12066917
Interquartile range (IQR)0.015696258

Descriptive statistics

Standard deviation0.01366199
Coefficient of variation (CV)8.4627905
Kurtosis3.1444567
Mean0.00161436
Median Absolute Deviation (MAD)0.0077923005
Skewness0.53315983
Sum0.60699936
Variance0.00018664998
MonotonicityNot monotonic
2024-07-03T23:51:46.701946image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.002226290179 1
 
0.3%
-0.003222547374 1
 
0.3%
0.00567140032 1
 
0.3%
-0.002263409002 1
 
0.3%
0.02417488166 1
 
0.3%
-0.004013033762 1
 
0.3%
-0.01270011581 1
 
0.3%
-0.007487607166 1
 
0.3%
-0.03578662771 1
 
0.3%
-0.005424129775 1
 
0.3%
Other values (366) 366
97.1%
ValueCountFrequency (%)
-0.04802004898 1
0.3%
-0.04085746419 1
0.3%
-0.03579332312 1
0.3%
-0.03578662771 1
0.3%
-0.02924939039 1
0.3%
-0.02844095267 1
0.3%
-0.0266798246 1
0.3%
-0.02617044149 1
0.3%
-0.02538126164 1
0.3%
-0.02460553222 1
0.3%
ValueCountFrequency (%)
0.07264912559 1
0.3%
0.05981625254 1
0.3%
0.04692692173 1
0.3%
0.04327091763 1
0.3%
0.03706260689 1
0.3%
0.03679410172 1
0.3%
0.0350900897 1
0.3%
0.03410363052 1
0.3%
0.03257068341 1
0.3%
0.02910457233 1
0.3%

Target
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size24.3 KiB
1
205 
0
172 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters377
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 205
54.4%
0 172
45.6%

Length

2024-07-03T23:51:46.852599image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-03T23:51:46.999751image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
1 205
54.4%
0 172
45.6%

Most occurring characters

ValueCountFrequency (%)
1 205
54.4%
0 172
45.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 377
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 205
54.4%
0 172
45.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 377
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 205
54.4%
0 172
45.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 377
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 205
54.4%
0 172
45.6%

Interactions

2024-07-03T23:51:40.808731image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:24.981225image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:26.426660image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:27.590589image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:28.780730image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:30.066859image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:31.212398image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:32.491872image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:33.780866image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:36.114557image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:38.201862image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:39.640033image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:40.912043image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:25.105457image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:26.514606image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:27.681098image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:28.876456image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:30.156069image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:31.327272image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:32.588091image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:33.882782image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:36.353541image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:38.313309image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:39.743182image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:41.008153image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:25.238085image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:26.599384image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:27.768448image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:28.966023image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:30.248487image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:31.425344image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:32.681206image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:34.065574image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:36.561607image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:38.424205image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:39.848400image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:41.099578image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:25.366428image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:26.691838image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:27.857705image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:29.059406image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:30.339083image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:31.526791image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:32.778579image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:34.249968image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:36.765595image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:38.535842image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:39.952706image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:41.189275image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:25.489326image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:26.781378image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:27.950181image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:29.148663image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:30.438881image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:31.627476image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:32.870811image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:34.434205image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:36.960703image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:38.645809image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:40.053089image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:41.282182image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:25.596104image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:26.870445image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:28.044902image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:29.256772image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:30.530965image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:31.734084image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:32.964653image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:34.625907image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:37.154780image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:38.743275image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:40.139174image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:41.409042image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:25.715242image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:26.968832image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:28.197264image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:29.398586image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:30.632392image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:31.850031image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:33.073676image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:34.844753image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:37.378736image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:38.884992image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:40.239985image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:41.534450image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:25.828230image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:27.122861image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:28.308688image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:29.498538image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:30.728166image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:31.958734image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:33.179066image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:35.048697image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:37.587109image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:39.009823image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:40.339182image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:41.626495image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:25.910132image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:27.208988image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:28.393393image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:29.583172image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:30.827883image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:32.057138image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:33.378817image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:35.225200image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:37.768908image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:39.242579image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:40.439202image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:41.716820image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:26.006453image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:27.297414image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:28.483638image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:29.671409image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:30.923178image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:32.158325image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:33.474993image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:35.413014image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:37.922938image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:39.347318image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:40.523893image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:41.826094image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:26.136090image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:27.405093image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:28.589576image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:29.884501image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:31.032682image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:32.276000image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:33.585327image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:35.647655image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:38.023490image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:39.452057image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:40.628919image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:41.918751image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:26.330696image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:27.498480image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:28.689576image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:29.976488image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:31.119990image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:32.379107image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:33.680342image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:35.891858image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:38.109673image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:39.542131image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-03T23:51:40.710530image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-07-03T23:51:47.220326image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
CloseHighLowMA_10MA_20OpenReturnTargetVolatility_10Volatility_20Volumelow-highopen-close
Close1.0000.9960.9960.9470.8780.9910.0350.059-0.0350.132-0.2210.0520.029
High0.9961.0000.9960.9520.8830.996-0.0120.060-0.0280.134-0.1990.0160.088
Low0.9960.9961.0000.9490.8790.996-0.0070.000-0.0360.132-0.2350.0800.085
MA_100.9470.9520.9491.0000.9640.952-0.0860.000-0.0360.131-0.164-0.0070.134
MA_200.8780.8830.8790.9641.0000.883-0.0730.000-0.0010.146-0.107-0.0750.111
Open0.9910.9960.9960.9520.8831.000-0.0570.084-0.0310.134-0.2240.0510.145
Return0.035-0.012-0.007-0.086-0.073-0.0571.0000.0000.0260.0570.076-0.055-0.797
Target0.0590.0600.0000.0000.0000.0840.0001.000-0.0250.0680.061-0.011-0.042
Volatility_10-0.035-0.028-0.036-0.036-0.001-0.0310.026-0.0251.0000.4840.297-0.1910.019
Volatility_200.1320.1340.1320.1310.1460.1340.0570.0680.4841.0000.124-0.150-0.017
Volume-0.221-0.199-0.235-0.164-0.107-0.2240.0760.0610.2970.1241.000-0.615-0.074
low-high0.0520.0160.080-0.007-0.0750.051-0.055-0.011-0.191-0.150-0.6151.0000.043
open-close0.0290.0880.0850.1340.1110.145-0.797-0.0420.019-0.017-0.0740.0431.000

Missing values

2024-07-03T23:51:42.060201image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-03T23:51:42.285888image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-07-03T23:51:42.590812image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

OpenHighLowCloseVolumeopen-closelow-highMA_10Volatility_10MA_20Volatility_20ReturnTarget
Date
2023-01-03130.279999130.899994124.169998125.0700001121175005.209999-6.729996NaNNaNNaNNaNNaN1
2023-01-04126.889999128.660004125.080002126.360001891136000.529999-3.580002NaNNaNNaNNaN0.0103140
2023-01-05127.129997127.769997124.760002125.019997809627002.110001-3.009995NaNNaNNaNNaN-0.0106051
2023-01-06126.010002130.289993124.889999129.61999587754700-3.609993-5.399994NaNNaNNaNNaN0.0367941
2023-01-09130.470001133.410004129.889999130.149994707908000.320007-3.520004NaNNaNNaNNaN0.0040891
2023-01-10130.259995131.259995128.119995130.72999663896200-0.470001-3.139999NaNNaNNaNNaN0.0044561
2023-01-11131.250000133.509995130.460007133.49000569458900-2.240005-3.049988NaNNaNNaNNaN0.0211120
2023-01-12133.880005134.259995131.440002133.410004713796000.470001-2.819992NaNNaNNaNNaN-0.0005991
2023-01-13132.029999134.919998131.660004134.75999557809700-2.729996-3.259995NaNNaNNaNNaN0.0101191
2023-01-17134.830002137.289993134.130005135.94000263646600-1.110001-3.159988130.4549993.982377NaNNaN0.0087560
OpenHighLowCloseVolumeopen-closelow-highMA_10Volatility_10MA_20Volatility_20ReturnTarget
Date
2024-06-20213.929993214.240005208.850006209.679993861725004.250000-5.389999207.2079998.971839199.39549910.277889-0.0215130
2024-06-21210.389999211.889999207.110001207.4900052464214002.899994-4.779999208.5090007.786002200.22499910.225487-0.0104441
2024-06-24207.720001212.699997206.589996208.13999980727000-0.419998-6.110001209.6340006.650608201.2879999.8638370.0031331
2024-06-25209.149994211.380005208.610001209.070007567139000.079987-2.770004211.2290013.337343202.2425009.6329410.0044681
2024-06-26211.500000214.860001210.639999213.25000066213200-1.750000-4.220001211.8390013.054429203.4054999.4786950.0199931
2024-06-27214.690002215.740005212.350006214.100006497727000.589996-3.389999211.9420013.117273204.5960009.2368760.0039860
2024-06-28215.770004216.070007210.300003210.619995825427005.150009-5.770004211.5800003.029722205.5625008.770867-0.0162541
2024-07-01212.089996217.509995211.919998216.75000060402900-4.660004-5.589996212.0060003.443173206.7875008.5210540.0291051
2024-07-02216.149994220.380005215.100006220.27000458046200-4.120010-5.279999212.3660004.108850208.0995008.4733520.0162401
2024-07-03220.000000221.550003219.029999221.55000337369800-1.550003-2.520004213.0920015.025681209.4595008.3320290.0058110